Mandrake

Mandrake performs dimensional reduction and embedding of microbial genomic datasets, including millions of whole genomes, to visualize population structure and genetic diversity in population genomics studies.


Key Features:

  • Dimensional Reduction Methodology: Mandrake employs an efficient implementation of dimensional reduction techniques tailored for large-scale population genomics to transform complex genomic datasets into low-dimensional representations.
  • Data Modalities Compatibility: Mandrake processes multiple sequence alignments, genome assemblies, and gene content estimates across genomes.
  • Visualization of Population Structure: Mandrake embeds genomic data into low-dimensional spaces to enable rapid exploration and visualization of microbial population structures.
  • Application to Major Pathogens: Mandrake has been applied to datasets representing major pathogens to support analyses of pathogen evolution and spread.

Scientific Applications:

  • Epidemiology: Mandrake elucidates genetic relationships and diversity among pathogen strains to aid outbreak tracking and transmission inference.
  • Evolutionary Biology: Mandrake supports study of evolutionary patterns within microbial populations, informing analyses of adaptation and speciation.
  • Genomic Surveillance: Mandrake enables rapid assessment of population genomics data for genomic surveillance and public health response.

Methodology:

Efficient implementation of dimensional reduction techniques that embed multiple sequence alignments, genome assemblies, and gene content estimates into a low-dimensional space for visualization of population structure.

Topics

Details

License:
MIT
Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Python, C++, C, JavaScript
Added:
4/25/2022
Last Updated:
4/25/2022

Operations

Publications

Lees JA, Tonkin-Hill G, Yang Z, Corander J. Mandrake: visualising microbial population structure by embedding millions of genomes into a low-dimensional representation. Unknown Journal. 2021. doi:10.1101/2021.10.28.466232.

Documentation

Links